diff --git a/docsrc/contents/smt.rst b/docsrc/contents/smt.rst
index 8efa43c0b..88d8ef546 100644
--- a/docsrc/contents/smt.rst
+++ b/docsrc/contents/smt.rst
@@ -528,11 +528,13 @@ Comparing GMPEs
         [models.AkkarEtAlRjb2014]
             lt_weight_gmc2_plot_lt_only = 0.50
             
+        # Also specify a GMM to compute ratios of the attenuation against (GMM/baseline)
+        [ratios_baseline_gmm.BooreEtAl2020]
+         
         [custom_colors]
         custom_colors_flag = 'False' # Set to "True" for custom colours in plots
         custom_colors_list = ['lime', 'dodgerblue', 'gold', '0.8']
             
-            
 3. Trellis Plots 
 
    Now that we have defined our inputs for GMPE comparison, we can use each tool within the Comparison module to evaluate how similar the GMPEs predict ground-motion for a given ground-shaking scenario.
@@ -573,10 +575,21 @@ Comparing GMPEs
        > comp.plot_spectra(filename, output_directory, obs_spectra='spectra_chamoli_1991_station_UKHI.csv') 
 
     Response spectra plots for input parameters specified in toml file:
-        .. image:: /contents/smt_images/ObsSpectra.png
-      
+        .. image:: /contents/smt_images/ObsSpectra.png      
+
+6. Plot of ratios of attenuation curves
+
+   The ratios of the median predictions from each GMM and a baseline GMM (specified in the ``.toml`` - see above) can also be plotted. An example is provided in the demo files:
+
+    .. code-block:: ini
+    
+       > # Plot ratios of median attenuation curves for each GMM/median attenuation curves for baseline GMM
+       > comp.plot_ratios(filename, output_directory) 
+
+    Ratio plots for input parameters specified in toml file (note that here the baseline GMM is BooreEtAl2014):
+        .. image:: /contents/smt_images/RatioPlots.png      
 
-6. Sammon's Maps
+7. Sammon's Maps
 
    We can plot Sammon's Maps to examine how similar the medians (and 16th and 84th percentiles) of predicted ground-motion of each GMPE are (see Sammon, 1969 and Scherbaum et al. 2010 for more details on the Sammon's mapping procedure).
    
@@ -592,7 +605,7 @@ Comparing GMPEs
     Sammon's Maps (median predicted ground-motion) for input parameters specified in toml file:
        .. image:: /contents/smt_images/Median_SammonMaps.png
     
-7. Hierarchical Clustering
+8. Hierarchical Clustering
 
    Dendrograms can be plotted as an alternative tool to evaluate how similarly the predicted ground-motion is by each GMPE.
    
@@ -608,7 +621,7 @@ Comparing GMPEs
     Dendrograms (median predicted ground-motion) for input parameters specified in toml file:
        .. image:: /contents/smt_images/Median_Clustering.png
          
-8. Matrix Plots of Euclidean Distance
+9. Matrix Plots of Euclidean Distance
 
    In addition to Sammon's Maps and hierarchical clustering, we can also plot the Euclidean distance between the predicted ground-motions by each GMPE in a matrix plot.
    
@@ -624,7 +637,7 @@ Comparing GMPEs
     Matrix plots of Euclidean distance between GMPEs (median predicted ground-motion) for input parameters specified in toml file:
        .. image:: /contents/smt_images/Median_Euclidean.png
     
-9. Using ModifiableGMPE to modify GMPEs within a ``.toml``. 
+10. Using ModifiableGMPE to modify GMPEs within a ``.toml``. 
 
    In addition to specifying predefined arguments for each GMPE, the user can also modify GMPEs using ModifiableGMPE (found in ``oq-engine.openquake.hazardlib.gsim.mgmpe.modifiable_gmpe``).
    
diff --git a/docsrc/contents/smt_images/RatioPlots.png b/docsrc/contents/smt_images/RatioPlots.png
new file mode 100644
index 000000000..fa3afbde6
Binary files /dev/null and b/docsrc/contents/smt_images/RatioPlots.png differ
diff --git a/openquake/smt/comparison/compare_gmpes.py b/openquake/smt/comparison/compare_gmpes.py
index 11d12da7d..1d27c42ff 100644
--- a/openquake/smt/comparison/compare_gmpes.py
+++ b/openquake/smt/comparison/compare_gmpes.py
@@ -28,8 +28,8 @@
 
 from openquake.hazardlib.imt import from_string
 from openquake.smt.comparison.utils_compare_gmpes import (
-    plot_trellis_util, plot_spectra_util, plot_cluster_util, plot_sammons_util,
-    plot_euclidean_util, compute_matrix_gmpes)
+    plot_trellis_util, plot_spectra_util, plot_ratios_util, plot_cluster_util,
+    plot_sammons_util, plot_euclidean_util, compute_matrix_gmpes)
 
 
 class Configurations(object):
@@ -45,7 +45,7 @@ def __init__(self, filename):
         # Import parameters for comparative plots from .toml file
         config_file = toml.load(filename) 
         
-        # Get input params from .toml file
+        # Get general params
         self.eshm20_region = config_file['general']['eshm20_region']
         self.minR = config_file['general']['minR']
         self.maxR = config_file['general']['maxR']
@@ -54,11 +54,7 @@ def __init__(self, filename):
         self.Nstd = config_file['general']['Nstd']
         self.max_period = config_file['general']['max_period']
         
-        self.custom_color_flag = config_file['custom_colors'][
-            'custom_colors_flag']
-        self.custom_color_list = config_file['custom_colors'][
-            'custom_colors_list']
-        
+        # Get site params
         self.Vs30 = config_file['site_properties']['vs30']
         self.Z1 = config_file['site_properties']['Z1']
         self.Z25 = config_file['site_properties']['Z25']
@@ -66,6 +62,7 @@ def __init__(self, filename):
         self.up_or_down_dip = float(up_or_down_dip)
         self.region = config_file['site_properties']['region']
         
+        # Get rupture params
         self.trt = config_file['source_properties']['trt']
         if self.trt == 'None':
             self.trt = None
@@ -75,9 +72,14 @@ def __init__(self, filename):
         self.strike = config_file['source_properties']['strike']
         self.dip = config_file['source_properties']['dip']
         self.rake = config_file['source_properties']['rake']
-
         self.aratio = config_file['source_properties']['aratio']
         
+        # Get custom colors
+        self.custom_color_flag = config_file['custom_colors'][
+            'custom_colors_flag']
+        self.custom_color_list = config_file['custom_colors'][
+            'custom_colors_list']
+
         # One set of magnitudes for use in trellis plots
         self.trellis_and_rs_mag_list = config_file['source_properties'][
             'trellis_and_rs_mag_list']
@@ -106,87 +108,148 @@ def __init__(self, filename):
         for idx, imt in enumerate(self.imt_list):
             self.imt_list[idx] = from_string(str(self.imt_list[idx]))  
         
-        # Get model labels
-        self.gmpe_labels = config_file['gmpe_labels']['gmpes_label']
+        # Get models and model labels
+        (self.gmpe_labels, self.gmpes_list, self.baseline_gmm) = get_gmpes(
+            config_file)
+
+        # Get lt weights
+        (self.lt_weights_gmc1, self.lt_weights_gmc2, self.lt_weights_gmc3,
+         self.lt_weights_gmc4) = get_lt_weights(self.gmpes_list)
+
+
+def get_gmpes(config_file):
+    """
+    Extract strings of the GMPEs from the configuration file. Also get the 
+    labels used in Sammons maps, Clustering (dendrograms) and Euclidean distance
+    matrix plots. The baseline GMM for computing ratios with is also extracted
+    if specified within the toml file.
+    """
+    # Get the GMPEs
+    gmpe_labels = config_file['gmpe_labels']['gmpes_label']
+    gmpe_list = []
+    config = copy.deepcopy(config_file)
+    for key in config['models']:
+        value = get_model(key, config['models'])
+        gmpe_list.append(value.strip())
+
+    # Check number of GMPEs matches number of GMPE labels
+    if len(gmpe_list) != len(gmpe_labels):
+        raise ValueError("Number of labels must match number of GMPEs.")
+
+    # Get the baseline GMPE used to compute ratios of GMPEs with if required
+    if 'ratios_baseline_gmm' in config_file.keys():
+        if len(config_file['ratios_baseline_gmm']) > 1:
+            raise ValueError('Only one baseline GMPE should be specified.')
+        for key in config_file['ratios_baseline_gmm']:
+            baseline_gmm = get_model(key, config['ratios_baseline_gmm'])
+    else:
+        baseline_gmm = None
+
+    return gmpe_labels, gmpe_list, baseline_gmm
+
+
+def get_model(key, models):
+    """
+    Get the model from the toml in the string format required to create an
+    OpenQuake gsim object from within mgmpe_check (in utils_gmpes.py)
+    """
+    # If the key contains a number we take the second part
+    if re.search("^\\d+\\-", key):
+        tmp = re.sub("^\\d+\\-", "", key)
+        value = f"[{tmp}] "
+    else:
+        value = f"[{key}] "
+    if len(models[key]):
+        models[key].pop('style', None)
+        value += '\n' + str(toml.dumps(models[key]))
+    return value.strip()
+
+
+def get_lt_weights(gmpe_list):
+    """
+    Manage the logic tree weight assigned for each GMPE in the toml (if any)
+    """
+    # If weight is assigned to a GMPE get it + check sum of weights for 
+    # GMPEs with weights allocated is about 1
+    weights = [{}, {}, {}, {}]
+    for gmpe in gmpe_list:
+        if 'lt_weight' in gmpe:
+            split_gmpe_str = str(gmpe).splitlines()
+            for idx, component in enumerate(split_gmpe_str):
+                if 'lt_weight_gmc1' in component:
+                    weights[0][gmpe] = float(split_gmpe_str[
+                        idx].split('=')[1])
+                if 'lt_weight_gmc2' in component:
+                    weights[1][gmpe] = float(split_gmpe_str[
+                        idx].split('=')[1])                       
+                if 'lt_weight_gmc3' in component:
+                    weights[2][gmpe] = float(split_gmpe_str[
+                        idx].split('=')[1])
+                if 'lt_weight_gmc4' in component:
+                    weights[3][gmpe] = float(split_gmpe_str[
+                        idx].split('=')[1])
         
-        # Get models
-        gmpes_list_initial = []
-        config = copy.deepcopy(config_file)
-        for key in config['models']:
-            
-            # If the key contains a number we take the second part
-            if re.search("^\\d+\\-", key):
-                tmp = re.sub("^\\d+\\-", "", key)
-                value = f"[{tmp}] "
-            else:
-                value = f"[{key}] "
-            if len(config['models'][key]):
-               config['models'][key].pop('style', None)
-               value += '\n' + str(toml.dumps(config['models'][key]))
-            value = value.strip()
-            gmpes_list_initial.append(value.strip())
-            
-        self.gmpes_list = []
-        for idx, gmpe in enumerate(gmpes_list_initial):
-            self.gmpes_list.append(gmpes_list_initial[idx])
-
-        # Check number of GMPEs matches number of GMPE labels
-        if len(self.gmpes_list) != len(self.gmpe_labels):
-            raise ValueError("Number of labels must match number of GMPEs.")
-
-        # If weight is assigned to a GMPE get it + check sum of weights for 
-        # GMPEs with weights allocated = 1
-        weights = [{}, {}, {}, {}]
-        for gmpe in self.gmpes_list:
-            if 'lt_weight' in gmpe:
-                split_gmpe_str = str(gmpe).splitlines()
-                for idx, component in enumerate(split_gmpe_str):
-                    if 'lt_weight_gmc1' in component:
-                        weights[0][gmpe] = float(split_gmpe_str[
-                            idx].split('=')[1])
-                    if 'lt_weight_gmc2' in component:
-                        weights[1][gmpe] = float(split_gmpe_str[
-                            idx].split('=')[1])                       
-                    if 'lt_weight_gmc3' in component:
-                        weights[2][gmpe] = float(split_gmpe_str[
-                            idx].split('=')[1])
-                    if 'lt_weight_gmc4' in component:
-                        weights[3][gmpe] = float(split_gmpe_str[
-                            idx].split('=')[1])
-            
-        # Check weights for each logic tree (if present) equal 1.0
-        msg = "Sum of GMC logic tree weights must be 1.0"
-        if weights[0] != {}:
-            check_weights_gmc1 = np.array(pd.Series(weights[0]))
-            lt_total_wt_gmc1 = np.sum(check_weights_gmc1, axis=0)
-            assert abs(lt_total_wt_gmc1-1.0) < 1e-10, msg
-            self.lt_weights_gmc1 = weights[0]
-        else:
-            self.lt_weights_gmc1 = None
+    # Check weights for each logic tree (if present) equal 1.0
+    msg = "Sum of GMC logic tree weights must be 1.0"
+    if weights[0] != {}:
+        check_weights_gmc1 = np.array(pd.Series(weights[0]))
+        lt_total_wt_gmc1 = np.sum(check_weights_gmc1, axis=0)
+        assert abs(lt_total_wt_gmc1-1.0) < 1e-10, msg
+        lt_weights_gmc1 = weights[0]
+    else:
+        lt_weights_gmc1 = None
+    
+    if weights[1] != {}:
+        check_weights_gmc2 = np.array(pd.Series(weights[1]))
+        lt_total_wt_gmc2 = np.sum(check_weights_gmc2, axis=0)
+        assert abs(lt_total_wt_gmc2-1.0) < 1e-10, msg
+        lt_weights_gmc2 = weights[1]
+    else:
+        lt_weights_gmc2 = None
+
+    if weights[2] != {}:
+        check_weights_gmc3 = np.array(pd.Series(weights[2]))
+        lt_total_wt_gmc3 = np.sum(check_weights_gmc3, axis=0)
+        assert abs(lt_total_wt_gmc3-1.0) < 1e-10, msg
+        lt_weights_gmc3 = weights[2]
+    else:
+        lt_weights_gmc3 = None
         
-        if weights[1] != {}:
-            check_weights_gmc2 = np.array(pd.Series(weights[1]))
-            lt_total_wt_gmc2 = np.sum(check_weights_gmc2, axis=0)
-            assert abs(lt_total_wt_gmc2-1.0) < 1e-10, msg
-            self.lt_weights_gmc2 = weights[1]
-        else:
-            self.lt_weights_gmc2 = None
-
-        if weights[2] != {}:
-            check_weights_gmc3 = np.array(pd.Series(weights[2]))
-            lt_total_wt_gmc3 = np.sum(check_weights_gmc3, axis=0)
-            assert abs(lt_total_wt_gmc3-1.0) < 1e-10, msg
-            self.lt_weights_gmc3 = weights[2]
-        else:
-            self.lt_weights_gmc3 = None
+    if weights[3] != {}:
+        check_weights_gmc4 = np.array(pd.Series(weights[3]))
+        lt_total_wt_gmc4 = np.sum(check_weights_gmc4, axis=0)
+        assert abs(lt_total_wt_gmc4-1.0) < 1e-10, msg
+        lt_weights_gmc4 = weights[3]
+    else:
+        lt_weights_gmc4 = None
+
+    return lt_weights_gmc1, lt_weights_gmc2, lt_weights_gmc3, lt_weights_gmc4
+
+
+def assign_depths_per_mag_bin(config_file, mag_array):
+    """
+    For each magnitude considered within the Sammons Maps, Euclidean distance
+    and clustering plots assign a depth
+    """
+    # Create dataframe of depth to assign per mag bin
+    non_trellis_or_spectra_depths = pd.DataFrame(config_file[
+        'mag_values_non_trellis_or_spectra_functions'][
+            'non_trellis_or_spectra_depths'], columns=['mag','depth'])
             
-        if weights[3] != {}:
-            check_weights_gmc4 = np.array(pd.Series(weights[3]))
-            lt_total_wt_gmc4 = np.sum(check_weights_gmc4, axis=0)
-            assert abs(lt_total_wt_gmc4-1.0) < 1e-10, msg
-            self.lt_weights_gmc4 = weights[3]
-        else:
-            self.lt_weights_gmc4 = None
+    # Round each mag in mag_array to closest integer
+    mag_to_nearest_int = pd.Series(dtype='float')
+    for mag in mag_array:
+        mag_to_nearest_int[mag] = np.round(mag+0.001)
+
+    # Assign depth to each mag in mag_array using rounded mags
+    depth_array_initial = []
+    for idx_mag, rounded_mag in enumerate(mag_to_nearest_int):
+        for idx, val in enumerate(non_trellis_or_spectra_depths['mag']):
+            if rounded_mag == non_trellis_or_spectra_depths['mag'][idx]:
+                depth_to_store = non_trellis_or_spectra_depths['depth'][idx]
+                depth_array_initial.append(depth_to_store)
+    
+    return pd.Series(depth_array_initial) 
 
 
 def plot_trellis(filename, output_directory):
@@ -196,7 +259,6 @@ def plot_trellis(filename, output_directory):
         toml file providing configuration for use within comparative
         plotting methods.
     """ 
-    # Generate config object
     config = Configurations(filename)
     
     store_gmm_curves = plot_trellis_util(config, output_directory) 
@@ -215,7 +277,6 @@ def plot_spectra(filename, output_directory, obs_spectra=None):
         csv of an observed spectra to plot and associated event information.
         An example file can be found in openquake.smt.tests.file_samples.
     """
-    # Generate config object
     config = Configurations(filename)
     
     store_gmc_lts = plot_spectra_util(config, output_directory, obs_spectra)
@@ -223,6 +284,23 @@ def plot_spectra(filename, output_directory, obs_spectra=None):
     return store_gmc_lts
 
 
+def plot_ratios(filename, output_directory):
+    """
+    Plot ratio (GMPE median attenuation/baseline GMPE median attenuation) for
+    given run configuration
+    :param  filename:
+        toml file providing configuration for use within comparative
+        plotting methods.
+    """ 
+    config = Configurations(filename)
+
+    if config.baseline_gmm is None:
+        raise ValueError(
+            'User must specify a baseline GMPE to generate ratio plots')
+    
+    plot_ratios_util(config, output_directory)
+
+
 def plot_cluster(filename, output_directory):
     """
     Plot hierarchical clusters of (1) median, (2) 84th percentile and (3) 16th
@@ -231,7 +309,6 @@ def plot_cluster(filename, output_directory):
         toml file providing configuration for use within comparative
         plotting methods.
     """ 
-    # Generate config object with each set of run parameters
     config = Configurations(filename)
     
     if len(config.gmpes_list) < 2:
@@ -266,7 +343,6 @@ def plot_sammons(filename, output_directory):
         toml file providing configuration for use within comparative
         plotting methods.
     """ 
-    # Generate config object with each set of run parameters
     config = Configurations(filename)
     
     if len(config.gmpes_list) < 2:
@@ -302,7 +378,6 @@ def plot_euclidean(filename, output_directory):
         toml file providing configuration for use within comparative
         plotting methods.    
     """ 
-    # Generate config object
     config = Configurations(filename)
     
     if len(config.gmpes_list) < 2:
@@ -325,32 +400,4 @@ def plot_euclidean(filename, output_directory):
     
     plot_euclidean_util(config.imt_list, config.gmpe_labels, mtxs_16th_perc,
                         os.path.join(output_directory,'16th_perc_Euclidean.png'),
-                        mtxs_type='16th_perc')
-    
-    
-def assign_depths_per_mag_bin(config_file, mag_array):
-    """
-    For each magnitude considered within the Sammons Maps, Euclidean distance
-    and clustering plots assign a depth
-    """
-    # Create dataframe of depth to assign per mag bin
-    non_trellis_or_spectra_depths = pd.DataFrame(config_file[
-        'mag_values_non_trellis_or_spectra_functions'][
-            'non_trellis_or_spectra_depths'], columns=['mag','depth'])
-            
-    # Round each mag in mag_array to closest integer
-    mag_to_nearest_int = pd.Series(dtype='float')
-    for mag in mag_array:
-        mag_to_nearest_int[mag] = np.round(mag+0.001)
-
-    # Assign depth to each mag in mag_array using rounded mags
-    depth_array_initial = []
-    for idx_mag, rounded_mag in enumerate(mag_to_nearest_int):
-        for idx, val in enumerate(non_trellis_or_spectra_depths['mag']):
-            if rounded_mag == non_trellis_or_spectra_depths['mag'][idx]:
-                depth_to_store = non_trellis_or_spectra_depths['depth'][idx]
-                depth_array_initial.append(depth_to_store)
-        
-    depths = pd.Series(depth_array_initial) 
-    
-    return depths
\ No newline at end of file
+                        mtxs_type='16th_perc')
\ No newline at end of file
diff --git a/openquake/smt/comparison/utils_compare_gmpes.py b/openquake/smt/comparison/utils_compare_gmpes.py
index 3d87786cc..cad677955 100644
--- a/openquake/smt/comparison/utils_compare_gmpes.py
+++ b/openquake/smt/comparison/utils_compare_gmpes.py
@@ -45,13 +45,19 @@ def plot_trellis_util(config, output_directory):
     # Median, plus sigma, minus sigma per gmc for up to 4 gmc logic trees
     gmc_p= [[{}, {}, {}], [{}, {}, {}], [{}, {}, {}], [{}, {}, {}]]
     
-    # Get model weights + basin params + colors + config key
+    # Get basin params
     Z1, Z25 = get_z1_z25(config.Z1, config.Z25, config.Vs30, config.region)
-    colors = get_cols(config.custom_color_flag, config.custom_color_list) 
+
+    # Get lt weights
     lt_weights = [config.lt_weights_gmc1, config.lt_weights_gmc2,
                   config.lt_weights_gmc3, config.lt_weights_gmc4]
-    cfg_key = 'vs30 = %s m/s, GMM sigma epsilon = %s' % (
-        config.Vs30, config.Nstd)
+    
+    # Get config key
+    cfg_key = 'vs30 = %s m/s, GMM sigma epsilon = %s' % (config.Vs30,
+                                                         config.Nstd)
+    
+    # Get colours
+    colors = get_colors(config.custom_color_flag, config.custom_color_list) 
     
     # Compute attenuation curves
     store_gmm_curves, store_per_imt = {}, {} # For exporting gmm att curves
@@ -64,6 +70,19 @@ def plot_trellis_util(config, output_directory):
         for l, m in enumerate(mag_list):
             fig.add_subplot(
                 len(config.imt_list), len(mag_list), l+1+n*len(mag_list))
+
+            # get ztor
+            if config.ztor is not None:
+                ztor_m = config.ztor[l]
+            else:
+                ztor_m = None
+            
+            # Get gmpe params
+            strike_g, dip_g, depth_g, aratio_g = _param_gmpes(
+                config.strike, config.dip, dep_list[l], config.aratio,
+                config.rake, config.trt) 
+
+            # Per GMPE get attenuation curves
             lt_vals_gmc = [{}, {}, {}, {}]
             store_per_gmpe = {}
             for g, gmpe in enumerate(config.gmpes_list): 
@@ -75,17 +94,6 @@ def plot_trellis_util(config, output_directory):
                 # Perform mgmpe check
                 gmm = mgmpe_check(gmpe)
                 
-                # ZTOR value
-                if config.ztor is not None:
-                    ztor_m = config.ztor[l]
-                else:
-                    ztor_m = None
-                
-                # Get gmpe params
-                strike_g, dip_g, depth_g, aratio_g = _param_gmpes(
-                    config.strike, config.dip, dep_list[l], config.aratio,
-                    config.rake, config.trt) 
-                
                 # Get attenuation curves
                 mean, std, r_vals, tau, phi = att_curves(gmm, dep_list[l], m,
                                                          aratio_g, strike_g,
@@ -105,27 +113,14 @@ def plot_trellis_util(config, output_directory):
                 minus_sigma = np.exp(mean-config.Nstd*std[0])
                 
                 # Plot predictions and get lt weighted predictions
-                lt_vals_gmc = trellis_data(gmpe, r_vals, mean,plus_sigma,
-                                           minus_sigma, col, i, m, config.Nstd,
+                lt_vals_gmc = trellis_data(gmpe, r_vals, mean, plus_sigma,
+                                           minus_sigma, col, config.Nstd,
                                            lt_vals_gmc, lt_weights)
                 
+                # Get unit of imt for the store
+                unit = get_imtl_unit_for_trellis_store(i)
+
                 # Store per gmpe
-                if str(i) in ['PGD', 'SDi']:
-                    unit = 'cm' # PGD, inelastic spectral displacement
-                elif str(i) in ['PGV']:
-                    unit = 'cm/s' # PGV
-                elif str(i) in ['IA']:
-                    unit = 'm/s' # Arias intensity
-                elif str(i) in ['RSD', 'RSD595', 'RSD575', 'RSD2080', 'DRVT']:
-                    unit = 's' # Relative significant duration, DRVT
-                elif str(i) in ['CAV']:
-                    unit = 'g-sec' # Cumulative absolute velocity
-                elif str(i) in ['MMI']:
-                    unit = 'MMI' # Modified Mercalli Intensity
-                elif str(i) in ['FAS', 'EAS']:
-                    pyplot.ylabel(str(i) + ' (Hz)') # Fourier/Eff. Amp. Spectrum
-                else:
-                    unit = 'g' # PGA, SA, AvgSA
                 store_per_gmpe[gmpe]['median (%s)' % unit] = np.exp(mean)
                 store_per_gmpe[gmpe]['sigma (ln)'] = std
                 if config.Nstd != 0:
@@ -185,16 +180,17 @@ def plot_spectra_util(config, output_directory, obs_spectra):
         obs_spectra = pd.read_csv(obs_spectra)
         max_period, eq_id, st_id = load_obs_spectra(obs_spectra)
     else:
+        max_period = config.max_period
         obs_spectra, eq_id, st_id = None, None, None
         
     # Get gmc lt weights, imts, periods and basin params
     gmc_weights = [config.lt_weights_gmc1, config.lt_weights_gmc2,
                    config.lt_weights_gmc3, config.lt_weights_gmc4]
-    imt_list, periods = _get_imts(config.max_period)
+    imt_list, periods = _get_imts(max_period)
     Z1, Z25 = get_z1_z25(config.Z1, config.Z25, config.Vs30, config.region)
     
     # Get colours and make the figure
-    colors = get_cols(config.custom_color_flag, config.custom_color_list)     
+    colors = get_colors(config.custom_color_flag, config.custom_color_list)     
     figure = pyplot.figure(figsize=(len(mag_list)*5, len(config.dist_list)*4))
     
     # Set dicts to store values
@@ -210,13 +206,18 @@ def plot_spectra_util(config, output_directory, obs_spectra):
             
             ax1 = figure.add_subplot(
                 len(config.dist_list), len(mag_list), l+1+n*len(mag_list))
+        
+            strike_g, dip_g, depth_g, aratio_g = _param_gmpes(config.strike,
+                                                              config.dip,
+                                                              dep_list[l],
+                                                              config.aratio,
+                                                              config.rake,
+                                                              config.trt)
+
             for g, gmpe in enumerate(config.gmpes_list):     
                 rs_50p, sig, rs_ps, rs_ms = [], [], [], []
                 col = colors[g]
                 gmm = mgmpe_check(gmpe)
-                strike_g, dip_g, depth_g, aratio_g = _param_gmpes(
-                    config.strike, config.dip, dep_list[l],
-                    config.aratio, config.rake, config.trt)
                 
                 for k, imt in enumerate(imt_list): 
                     if config.ztor is not None:
@@ -308,6 +309,91 @@ def plot_spectra_util(config, output_directory, obs_spectra):
     return store_gmc_lts # Returned for unit tests of gmc lt values
 
 
+def plot_ratios_util(config, output_directory):
+    """
+    Generate ratio (GMPE median attenuation/baseline GMPE median attenuation) 
+    plots for given run configuration
+    """
+    # Get mag and dep lists
+    mag_list = config.trellis_and_rs_mag_list
+    dep_list = config.trellis_and_rs_depth_list
+
+    # Get basin params
+    Z1, Z25 = get_z1_z25(config.Z1, config.Z25, config.Vs30, config.region)
+    
+    # Get config key
+    cfg_key = 'vs30 = %s m/s, GMM sigma epsilon = %s' % (config.Vs30,
+                                                         config.Nstd)
+    
+    # Get colours
+    colors = get_colors(config.custom_color_flag, config.custom_color_list) 
+    
+    # Compute ratio curves
+    fig = pyplot.figure(figsize=(len(mag_list)*5, len(config.imt_list)*4))
+    ratio_store = []
+    for n, i in enumerate(config.imt_list):
+        for l, m in enumerate(mag_list):
+            fig.add_subplot(
+                len(config.imt_list), len(mag_list), l+1+n*len(mag_list))
+            
+            # ztor value
+            if config.ztor is not None:
+                ztor_m = config.ztor[l]
+            else:
+                ztor_m = None
+            
+            # Get gmpe params
+            strike_g, dip_g, depth_g, aratio_g = _param_gmpes(
+                config.strike, config.dip, dep_list[l], config.aratio,
+                config.rake, config.trt) 
+
+            # Load the baseline GMM and compute baseline
+            baseline = mgmpe_check(config.baseline_gmm)
+
+            # Get baseline GMM attenuation curves
+            results = att_curves(baseline, dep_list[l], m, aratio_g,
+                                 strike_g, dip_g, config.rake,
+                                 config.Vs30, Z1, Z25, config.maxR, 1, i, ztor_m,
+                                 config.eshm20_region, config.dist_type,
+                                 config.trt, config.up_or_down_dip)
+            b_mean = results[0][0][0]
+
+            # Now compute ratios for each GMM
+            for g, gmpe in enumerate(config.gmpes_list):        
+                
+                # Perform mgmpe check
+                col = colors[g]         
+                gmm = mgmpe_check(gmpe)
+                
+                # Get attenuation curves for the GMM
+                results = att_curves(gmm, dep_list[l], m, aratio_g, strike_g,
+                                     dip_g, config.rake, config.Vs30, Z1, Z25,
+                                     config.maxR, 1, i, ztor_m,
+                                     config.eshm20_region, config.dist_type,
+                                     config.trt, config.up_or_down_dip)
+
+                # Get mean and r_vals
+                mean = results[0][0][0]
+                r_vals = results[2]
+
+                # Compute GMM/baseline
+                ratio = np.exp(mean)/np.exp(b_mean)
+                ratio_store.append(ratio)
+
+                # Plot ratios
+                pyplot.semilogy(r_vals, ratio, color = col, linewidth=2, 
+                            linestyle='-', label=gmpe)
+                
+                # Update plots
+                update_ratio_plots(config.dist_type, m, i, n, l, config.imt_list,
+                                   r_vals, config.minR, config.maxR)
+    
+    # Finalise plots
+    pyplot.legend(loc="center left", bbox_to_anchor=(1.1, 1.05), fontsize='16')
+    pyplot.savefig(os.path.join(output_directory, 'RatioPlots.png'),
+                   bbox_inches='tight', dpi=200, pad_inches=0.2)
+
+
 def compute_matrix_gmpes(config, mtxs_type):
     """
     Compute matrix of median ground-motion predictions for each gmpe for the
@@ -335,11 +421,14 @@ def compute_matrix_gmpes(config, mtxs_type):
             
                 gmm = mgmpe_check(gmpe)
 
-                strike_g, dip_g, depth_g, aratio_g = _param_gmpes(
-                    config.strike, config.dip, dep_list[l], config.aratio,
-                    config.rake, config.trt) 
+                strike_g, dip_g, depth_g, aratio_g = _param_gmpes(config.strike,
+                                                                  config.dip,
+                                                                  dep_list[l],
+                                                                  config.aratio,
+                                                                  config.rake,
+                                                                  config.trt) 
                 
-                # ZTOR                
+                # ztor              
                 if config.ztor is not None:
                     ztor_m = config.ztor[l]
                 else:
@@ -468,7 +557,7 @@ def plot_sammons_util(imt_list, gmpe_list, mtxs, namefig, custom_color_flag,
     mtxs, gmpe_list = matrix_mean(mtxs, imt_list, gmpe_list)
     
     # Setup
-    colors = get_cols(custom_color_flag, custom_color_list)
+    colors = get_colors(custom_color_flag, custom_color_list)
     texts = []
     if len(imt_list) < 3:
         nrows = 1
@@ -593,14 +682,12 @@ def plot_cluster_util(imt_list, gmpe_list, mtxs, namefig, mtxs_type):
 
 ### Utils for plots
 
-def get_cols(custom_color_flag, custom_color_list):
+def get_colors(custom_color_flag, custom_color_list):
     """
     Get list of colors for plots
     """
-    colors = ['g', 'b', 'y', 'lime', 'dodgerblue', 'gold', '0.8', '0.5', 'r',
-              'm', 'mediumseagreen', 'tab:pink', 'tab:orange', 'tab:purple',
-              'tab:brown', 'tab:pink', 'tab:red', 'tab:blue', 'tab:cyan',
-              'tab:olive', 'aquamarine']
+    colors = ['r', 'g', 'b', 'y', 'lime', 'dodgerblue', 'gold', '0.8', 'm', 'k',
+              'mediumseagreen', 'tab:orange', 'tab:purple', 'tab:brown', '0.5']
     
     if custom_color_flag == 'True':
         colors = custom_color_list
@@ -622,7 +709,7 @@ def get_z1_z25(Z1, Z25, Vs30, region):
 
 
 ### Trellis utils
-def trellis_data(gmpe, r_vals, mean,plus_sigma, minus_sigma, col, i, m, Nstd,
+def trellis_data(gmpe, r_vals, mean,plus_sigma, minus_sigma, col, Nstd,
                  lt_vals_gmc, lt_weights):
     """
     Plot predictions of a single GMPE (if required) and compute weighted
@@ -644,7 +731,7 @@ def trellis_data(gmpe, r_vals, mean,plus_sigma, minus_sigma, col, i, m, Nstd,
             pass
         elif gmpe in lt_weights[idx_gmc]:
             if lt_weights[idx_gmc][gmpe] is not None:
-                if Nstd != 0:
+                if Nstd > 0:
                     lt_vals_gmc[idx_gmc][gmpe] = {
                                 'median': np.exp(mean)*lt_weights[
                                     idx_gmc][gmpe],
@@ -680,7 +767,7 @@ def trel_logic_trees(idx_gmc, gmc, lt_vals_gmc, gmc_p, store_gmm_curves,
             'gmc logic tree curves per imt-mag'][lt_key][
                 'median (%s)' % unit] = median
         
-        if Nstd != 0:
+        if Nstd > 0:
             store_gmm_curves[
                 cfg_key]['gmc logic tree curves per imt-mag'][
                     lt_key]['median plus sigma (%s)' % unit
@@ -718,7 +805,7 @@ def lt_trel(r_vals, Nstd, i, m, dep, dip, rake, idx_gmc, lt_vals_gmc,
                 linestyle='--', label=label,
                 zorder=100)
     
-    if Nstd != 0:
+    if Nstd > 0:
         
         lt_plus_sigma_gmc = np.sum(lt_df_gmc[:].loc['plus_sigma'])
         lt_minus_sigma_gmc = np.sum(lt_df_gmc[:].loc['minus_sigma'])
@@ -775,7 +862,7 @@ def update_trellis_plots(m, i, n, l, minR, maxR, r_vals, imt_list, dist_type):
     elif str(i) in ['PGV']:
         pyplot.ylim(1, 650) # cm/s
     else:
-        print('User may want to manually specify y-axis limits')
+        print('User may want to manually specify y-axis limits for %s' % i)
 
     # xlims
     pyplot.loglog()
@@ -783,6 +870,31 @@ def update_trellis_plots(m, i, n, l, minR, maxR, r_vals, imt_list, dist_type):
     pyplot.xlim(np.max([min_r_val, minR]), maxR)
     
 
+def get_imtl_unit_for_trellis_store(i):
+    """
+    Return a string of the intensity measure type's physical units of
+    measurement
+    """
+    if str(i) in ['PGD', 'SDi']:
+        unit = 'cm' # PGD, inelastic spectral displacement
+    elif str(i) in ['PGV']:
+        unit = 'cm/s' # PGV
+    elif str(i) in ['IA']:
+        unit = 'm/s' # Arias intensity
+    elif str(i) in ['RSD', 'RSD595', 'RSD575', 'RSD2080', 'DRVT']:
+        unit = 's' # Relative significant duration, DRVT
+    elif str(i) in ['CAV']:
+        unit = 'g-sec' # Cumulative absolute velocity
+    elif str(i) in ['MMI']:
+        unit = 'MMI' # Modified Mercalli Intensity
+    elif str(i) in ['FAS', 'EAS']:
+        pyplot.ylabel(str(i) + ' (Hz)') # Fourier/Eff. Amp. Spectrum
+    else:
+        unit = 'g' # PGA, SA, AvgSA
+
+    return unit
+
+
 ### Spectra utils
 def _get_period_values_for_spectra_plots(max_period):
     """
@@ -865,7 +977,7 @@ def spectra_data(gmpe, Nstd, gmc_weights, rs_50p, rs_plus_sigma, rs_minus_sigma,
                 for idx, rs in enumerate(rs_50p):
                     rs_50p_w[idx] = rs_50p[idx]*gmc_weights[
                         idx_gmc][gmpe]
-                    if Nstd != 0:
+                    if Nstd > 0:
                         rs_plus_sigma_w[idx] = rs_plus_sigma[
                             idx]*gmc_weights[idx_gmc][gmpe]
                         rs_minus_sigma_w[idx] = rs_minus_sigma[
@@ -874,8 +986,8 @@ def spectra_data(gmpe, Nstd, gmc_weights, rs_50p, rs_plus_sigma, rs_minus_sigma,
                 # Store the weighted median for the GMPE
                 lt_vals[idx_gmc][gmpe] = {'median': rs_50p_w}
                 
-                # And if Nstd != 0 store these weighted branches too
-                if Nstd != 0:
+                # And if Nstd > 0 store these weighted branches too
+                if Nstd > 0:
                     lt_vals_plus[idx_gmc][gmpe,'p_sig'] = {
                         'plus_sigma': rs_plus_sigma_w}
                     lt_vals_minus[idx_gmc][gmpe,'m_sig'] = {
@@ -903,7 +1015,7 @@ def lt_spectra(ax1, gmpe, gmpe_list, Nstd, period, idx_gmc,
     # Plot   
     lt_per_imt_gmc, lt_plus_sig_per_imt, lt_minus_sig_per_imt = {}, {}, {}
     lt_df_gmc = pd.DataFrame(lt_vals_gmc, index=['median'])
-    if Nstd != 0:
+    if Nstd > 0:
         lt_plus_sig = pd.DataFrame(ltv_plus_sig, index=['plus_sigma'])
         lt_minus_sig = pd.DataFrame(ltv_minus_sig, index=['minus_sigma'])    
     wt_per_gmpe_gmc, wt_plus_sig, wt_minus_sig = {}, {}, {}
@@ -911,7 +1023,7 @@ def lt_spectra(ax1, gmpe, gmpe_list, Nstd, period, idx_gmc,
         if check in str(gmpe):
             wt_per_gmpe_gmc[gmpe] = np.array(pd.Series(
                 lt_df_gmc[gmpe].loc['median']))
-            if Nstd != 0:
+            if Nstd > 0:
                 wt_plus_sig[gmpe] = np.array(
                     pd.Series(lt_plus_sig[gmpe,'p_sig'].loc['plus_sigma']))
                 wt_minus_sig[gmpe] = np.array(
@@ -922,7 +1034,7 @@ def lt_spectra(ax1, gmpe, gmpe_list, Nstd, period, idx_gmc,
     lt_minus_sig = pd.DataFrame(wt_minus_sig, index=period)
     for idx, imt in enumerate(period):
         lt_per_imt_gmc[imt] = np.sum(lt_df_gmc.loc[imt])
-        if Nstd != 0:
+        if Nstd > 0:
             lt_plus_sig_per_imt[imt] = np.sum(lt_plus_sig.loc[imt])
             lt_minus_sig_per_imt[imt] = np.sum(lt_minus_sig.loc[imt])
     
@@ -931,7 +1043,7 @@ def lt_spectra(ax1, gmpe, gmpe_list, Nstd, period, idx_gmc,
              color=col, linestyle='--', label = label, zorder=100)
     
     # Plot mean plus sigma and mean minus sigma if required
-    if Nstd != 0:
+    if Nstd > 0:
         ax1.plot(period, np.array(pd.Series(lt_plus_sig_per_imt)),
                  linewidth=0.75, color=col, linestyle='-.', zorder=100)     
         ax1.plot(period, np.array(pd.Series(lt_minus_sig_per_imt)),
@@ -1007,6 +1119,27 @@ def save_spectra_plot(f1, obs_spectra, output_dir, eq_id, st_id):
 
 
 ### Utils for other plots
+def update_ratio_plots(dist_type, m, i, n, l, imt_list, r_vals, minR, maxR):
+    """
+    Add titles and axis labels to ratio plots
+    """
+    if dist_type == 'repi':
+        label = 'Repi (km)'
+    if dist_type == 'rrup':
+        label = 'Rrup (km)'
+    if dist_type == 'rjb':
+        label = 'Rjb (km)'
+    if dist_type == 'rhypo':
+        label = 'Rhypo (km)'
+    if n == 0: # Top row only
+        pyplot.title('Mw = ' + str(m), fontsize='16')
+    if n == len(imt_list)-1: # Bottom row only
+        pyplot.xlabel(label, fontsize='12')
+    if l == 0: # Left row only
+        pyplot.ylabel('GMM/baseline for %s' %str(i), fontsize='14')
+    min_r_val = min(r_vals[r_vals>=1])
+    pyplot.xlim(np.max([min_r_val, minR]), maxR)
+
 def matrix_mean(mtxs, imt_list, gmpe_list):
     """
     For a matrix of predicted ground-motions computed the arithmetic mean per
diff --git a/openquake/smt/demos/demo_comparison_analysis_inputs.toml b/openquake/smt/demos/demo_comparison_analysis_inputs.toml
index 50991c0c8..bb3cdfe7c 100644
--- a/openquake/smt/demos/demo_comparison_analysis_inputs.toml
+++ b/openquake/smt/demos/demo_comparison_analysis_inputs.toml
@@ -83,6 +83,9 @@ lt_weight_gmc2_plot_lt_only = 0.50
 [models.AkkarEtAlRjb2014]
 lt_weight_gmc2_plot_lt_only = 0.50
     
+# Also specify a GMM to compute ratios of the attenuation against (GMM/baseline)
+[ratios_baseline_gmm.BooreEtAl2020]
+
 [custom_colors]
 custom_colors_flag = 'False' # Set to "True" for custom colours in plots)
 custom_colors_list = ['lime', 'dodgerblue', 'gold', '0.8']
\ No newline at end of file
diff --git a/openquake/smt/demos/demo_comparison_script.py b/openquake/smt/demos/demo_comparison_script.py
index 85285c2de..7db3e2b83 100644
--- a/openquake/smt/demos/demo_comparison_script.py
+++ b/openquake/smt/demos/demo_comparison_script.py
@@ -23,12 +23,13 @@
     name_analysis = config_file['general']['name_analysis'] 
     output_directory = os.path.join(os.path.abspath(''),name_analysis)
 
-    # set the output
+    # Set the output
     if not os.path.exists(output_directory): os.makedirs(output_directory)
     
-    #Generate plots from config object
+    # Generate plots from config object
     attenuation_curve_data[file] = comp.plot_trellis(filename,output_directory)
     comp.plot_spectra(filename,output_directory)
+    comp.plot_ratios(filename, output_directory)
     comp.plot_cluster(filename,output_directory)
     comp.plot_sammons(filename,output_directory)
     comp.plot_euclidean(filename,output_directory)
diff --git a/openquake/smt/residuals/residual_plotter.py b/openquake/smt/residuals/residual_plotter.py
index 93f786786..24480c983 100755
--- a/openquake/smt/residuals/residual_plotter.py
+++ b/openquake/smt/residuals/residual_plotter.py
@@ -37,9 +37,9 @@
     residuals_density_distribution, likelihood, residuals_with_magnitude,
     residuals_with_vs30, residuals_with_distance, residuals_with_depth)
 
-colors = ['r', 'g', 'b', 'y','lime', 'dodgerblue', 'k', 'gold', '0.8',
-          'mediumseagreen', '0.5', 'tab:orange', 'tab:purple','tab:brown',
-          'tab:pink']
+
+colors = ['r', 'g', 'b', 'y', 'lime', 'dodgerblue', 'gold', '0.8', 'm', 'k',
+          'mediumseagreen', 'tab:orange', 'tab:purple', 'tab:brown', '0.5']
 
 
 class BaseResidualPlot(object):
diff --git a/openquake/smt/tests/comparison/comparison_test.py b/openquake/smt/tests/comparison/comparison_test.py
index 1a269d697..97c960764 100644
--- a/openquake/smt/tests/comparison/comparison_test.py
+++ b/openquake/smt/tests/comparison/comparison_test.py
@@ -26,7 +26,7 @@
 from openquake.smt.comparison import compare_gmpes as comp
 from openquake.smt.comparison.utils_compare_gmpes import (
     compute_matrix_gmpes, plot_trellis_util, plot_spectra_util,
-    plot_cluster_util, plot_sammons_util, plot_euclidean_util)
+    plot_ratios_util, plot_cluster_util, plot_sammons_util, plot_euclidean_util)
 
 
 # Base path
@@ -47,6 +47,7 @@
                 '[CampbellBozorgnia2014] \nlt_weight_gmc1 = 0.5',
                 '[BooreEtAl2014] \nlt_weight_gmc2_plot_lt_only = 0.5',
                 '[KothaEtAl2020] \nlt_weight_gmc2_plot_lt_only = 0.5']
+TARGET_BASELINE_GMPE = '[BooreEtAl2014]'
 TARGET_TRT = 'ASCR'
 TARGET_ZTOR = None
 
@@ -76,13 +77,13 @@ def test_configuration_object_check(self):
         the Configuration object, which stores the inputted parameters for
         each run.
         """
-        # Check each parameter matches target
+        # Load config
         config = comp.Configurations(self.input_file)
 
         # Check for target TRT
         self.assertEqual(config.trt, TARGET_TRT)
 
-        # Check for target ZTOR
+        # Check for target ztor
         self.assertEqual(config.ztor, TARGET_ZTOR)
 
         # Check for target Vs30
@@ -122,12 +123,15 @@ def test_configuration_object_check(self):
         for imt in range(0, len(config.imt_list)):
             self.assertEqual(str(config.imt_list[imt]), TARGET_IMTS[imt])
 
+        # Check baseline GMM used to compute ratios
+        self.assertEqual(config.baseline_gmm, TARGET_BASELINE_GMPE)
+
     def test_mtxs_median_calculation(self):
         """
         Check for matches bewteen the matrix of medians computed using
         compute_matrix_gmpes and those expected given the input parameters
         """
-        # Check each parameter matches target
+        # Load config
         config = comp.Configurations(self.input_file)
 
         # Get medians
@@ -147,7 +151,7 @@ def test_sammons_and_euclidean_distance_matrix_functions(self):
         """
         TARGET_GMPES.append('mean')  # Add mean here to gmpe_list
 
-        # Check each parameter matches target
+        # Load config
         config = comp.Configurations(self.input_file)
 
         # Get medians
@@ -188,7 +192,7 @@ def test_clustering_median(self):
         Check clustering functions for median predicted ground-motion of
         considered GMPEs in the configuration
         """
-        # Check each parameter matches target
+        # Load config
         config = comp.Configurations(self.input_file)
 
         # Get medians
@@ -213,7 +217,7 @@ def test_clustering_84th_perc(self):
         Check clustering of 84th percentile of predicted ground-motion of
         considered GMPEs in the configuration
         """
-        # Check each parameter matches target
+        # Load config
         config = comp.Configurations(self.input_file)
 
         # Get medians
@@ -239,7 +243,7 @@ def test_trellis_and_spectra_functions(self):
         executed. Also checks correct values are returned for the gmm
         attenuation curves and spectra.
         """
-        # Check each parameter matches target
+        # Load config
         config = comp.Configurations(self.input_file)
 
         # Trellis plots
@@ -286,9 +290,20 @@ def test_plot_observed_spectra(self):
         # Check target file created and outputted in expected location
         self.assertTrue(target_file_spectra)
 
+    def test_plot_ratios(self):
+        """
+        Test execution of plotting ratios (median GMM attenuation/median
+        baseline GMM attenuation). Correctness of values is not examined.
+        """
+        # Load config
+        config = comp.Configurations(self.input_file)
+
+        # Plot the ratios
+        plot_ratios_util(config, self.output_directory)
+
     @classmethod
     def tearDownClass(self):
         """
         Remove the test outputs
         """
-        shutil.rmtree(self.output_directory)
+        shutil.rmtree(self.output_directory)
\ No newline at end of file
diff --git a/openquake/smt/tests/comparison/data/compare_gmpe_inputs.toml b/openquake/smt/tests/comparison/data/compare_gmpe_inputs.toml
index 2aaf0a268..0c9ff3e6f 100644
--- a/openquake/smt/tests/comparison/data/compare_gmpe_inputs.toml
+++ b/openquake/smt/tests/comparison/data/compare_gmpe_inputs.toml
@@ -52,6 +52,9 @@ lt_weight_gmc2_plot_lt_only = 0.5
 [models.KothaEtAl2020]
 lt_weight_gmc2_plot_lt_only = 0.5
 
+# Baseline GMM to compute ratios of the attenuation against (GMM/baseline)
+[ratios_baseline_gmm.BooreEtAl2014]
+
 
 [custom_colors]
 custom_colors_flag = 'False' #By default set to "False" (set to "True" for custom colours)
diff --git a/openquake/smt/tests/comparison/data/mgmpe_inputs.toml b/openquake/smt/tests/comparison/data/mgmpe_inputs.toml
index 59cedb6b4..207790669 100644
--- a/openquake/smt/tests/comparison/data/mgmpe_inputs.toml
+++ b/openquake/smt/tests/comparison/data/mgmpe_inputs.toml
@@ -97,6 +97,11 @@ gmpe_table = 'NGAEast_FRANKEL_J15.hdf5' # use a gmpe table
 d_sigma = 100 # gmpe specific param
 kappa0 = 0.04
 
+[ratios_baseline_gmm.ModifiableGMPE] # Check mgmpe works for loading baseline model used in ratio plots
+gmpe = 'YenierAtkinson2015BSSA'
+sigma_model = 'al_atik_2015_sigma' # use Al Atik (2015) sigma model
+with_betw_ratio = 1.5
+
 [custom_colors]
 custom_colors_flag = 'False' # By default set to "False" (set to "True" for custom colours)
 custom_colors_list = ['lime','dodgerblue','gold','0.8']
\ No newline at end of file